Enhancing psychosomatic health using artificial intelligence-based treatment protocol: A data science-driven approach

Abstract

The present study opens an avenue for an improved holistic state of health. Several parameters related to an individual's cognitive interactions to manage stress have been explored. It induces multiple therapeutic interventions in an experimental setting to fulfill the same. This is a quantitative study in which relevant data are captured using a questionnaire and Brain-Computer Interaction (BCI) simultaneously. The research findings establish the role of significant factors that help to determine psychosomatic health.Data-driven models built using unique cognitive instances can augment psychosomatic health in terms of time, cost, and access. Since this study is based on a technological foundation defined by an electroencephalograph (EEG), it can further be scaled for other healthcare applications and incorporated into ‘Digital Twin.’ Using Artificial Intelligence (AI) based treatment protocol, the findings could be extended to the healthcare ecosystem.

Keywords

• Healthcare services
• Data science
• Machine learning
• Psychosomatic health
• Well-being